No abstract

With cardiovascular disease (CVD) remaining the primary cause of death worldwide, early detection of CVDs becomes essential. The intracardiac flow is an important component of ventricular function, motion kinetics, wash-out of ventricular chambers, and ventricular energetics. Coupling between Computational Fluid Dynamics (CFD) simulations and medical images can play a fundamental role in terms of patient-specific diagnostic tools. From a technical perspective, CFD simulations with moving boundaries could easily lead to negative volumes errors and the sudden failure of the simulation. The generation of high-quality 4D meshes (3D in space + time) with 1-to-1 vertex becomes essential to perform a CFD simulation with moving boundaries. In this context, we developed a semiautomatic morphing tool able to create 4D high-quality structured meshes starting from a segmented 4D dataset. To prove the versatility and efficiency, the method was tested on three different 4D datasets (Ultrasound, MRI, and CT) by evaluating the quality and accuracy of the resulting 4D meshes. Furthermore, an estimation of some physiological quantities is accomplished for the 4D CT reconstruction. Future research will aim at extending the region of interest, further automation of the meshing algorithm, and generating structured hexahedral mesh models both for the blood and myocardial volume.

Cardiovascular disease often occurs with silent and gradual alterations of cardiac blood flow that can lead to the onset of chronic pathological conditions. Image-based patient-specific Computational Fluid Dynamics (CFD) models allow for an extensive quantification of the flow field beyond the direct capabilities of medical imaging techniques that could support the clinicians in the early diagnosis, follow-up, and treatment planning of patients. Nonetheless, the large and impulsive kinematics of the left ventricle (LV) and the mitral valve (MV) pose relevant modeling challenges. Arbitrary Lagrangian-Eulerian (ALE) based computational fluid dynamics (CFD) methods struggle with the complex 3D mesh handling of rapidly moving valve leaflets within the left ventricle (LV). We, therefore, developed a Chimera-based (overset meshing) method to build a patient-specific 3D CFD model of the beating LV which includes a patient-inspired kinematic model of the mitral valve (LVMV). Simulations were performed with and without torsion. In addition, to evaluate how the intracardiac LV flow is impacted by the MV leaflet kinematics, a third version of the model without the MV was generated (LV with torsion). For all model versions, six cardiac cycles were simulated. All simulations demonstrated cycle-to-cycle variations that persisted after six cycles but were albeit marginal in terms of the magnitude of standard deviation of velocity and vorticity which may be related to the dissipative nature of the numerical scheme used. The MV was found to have a crucial role in the development of the intraventricular flow by enhancing the direct flow, the apical washout, and the propagation of the inlet jet towards the apical region. Consequently, the MV is an essential feature in the patient-specific CFD modeling of the LV. The impact of torsion was marginal on velocity, vorticity, wall shear stress, and energy loss, whereas it resulted to be significant in the evaluation of particle residence times. Therefore, including torsion could be considered in patient-specific CFD models of the LV, particularly when aiming to study stasis and residence time. We conclude that, despite some technical limitations encountered, the Chimera technique is a promising alternative for ALE methods for 3D CFD models of the heart that include the motion of valve leaflets.